Poverty Comparisons Over Time and Across Countries in Africa

Sahn, David E.; Stifel, David

doi:10.1016/s0305-750x(00)00075-9

Cited by 432 publications

(257 citation statements)

References 7 publications

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“…One factor with eigenvalue greater than 1 was extracted explaining 94% of the total variation. Given that all the included variables are closely related to households' wealth status, the first factor explaining 94% of the total variation is assumed to be our measure of wealth (McKenzie, 2005;Sahn & Stifel, 2000). Kaiser-Meyer-Olkin measure of sampling adequacy is 0.7 and Bartlett's test of sphericity has a value of 538.575 (df = 66, P < .000) indicating that the model fit is appropriate.…”

Section: Wealth and Poverty Measurementmentioning

confidence: 99%

“…Households who are below the 40 th percentile of the wealth index are categorized as poor and all others as non-poor. Sahn & Stifel (2000) and Fisher & Kandiwa (2014) also applied the asset poverty approach and used the 40 th percentile as a cut off-point for poverty categories. The descriptive statistics for the social network variables as well as the other control variables included in the econometric model are provided in Table 2.…”

Section: Wealth and Poverty Measurementmentioning

confidence: 99%

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Social Network Effects on Mobile Money Adoption in Uganda

Murendo

Wollni

Brauw

et al. 2017

The Journal of Development Studies

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. -551-3920212, fax: +49-551-3920203, e-mail: conrad.murendo@agr.uni-goettingen.de Abstract Social networks play a vital role in generating social learning and information exchange that can drive the diffusion of new financial innovations. This is particularly relevant for developing countries where education, extension and financial information services are underprovided. The recent introduction of mobile money in Africa represents a case where imperfect financial markets, weak extension services and information asymmetries limit the ability of rural households to make informed decisions to take advantage of mobile money innovation. This article identifies the role of social networks in the adoption of mobile money in Uganda. Using data from a survey of 477 rural households, a probit model is estimated controlling for household characteristics, correlated effects, and other possible information sources. Results suggest that learning within social networks helps disseminate information about mobile money and has enhanced its adoption. Compared to poor households, non-poor households rely more on social networks for information about mobile money. Mobile money adoption is likely to be enhanced if promotion programs reach more social networks. Terms of use: Documents in

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Section: Wealth and Poverty Measurementmentioning

confidence: 99%

Section: Wealth and Poverty Measurementmentioning

confidence: 99%

Social Network Effects on Mobile Money Adoption in Uganda

Murendo

Wollni

Brauw

et al. 2017

The Journal of Development Studies

View full text Add to dashboard Cite

show abstract

“…2) Socio-economic stratification of the standard of living The first step is to estimate an indicator of wealth for each household based on the weighted sum of various indicators of well-being [11]- [14]. Let's i X be the wealth indicator for the household i, ij x owned in basics needs j and by j α the weight of each basic need, the expression of i X is:…”

Section: ) Critical Assetsmentioning

confidence: 99%

“…According to Meulman'sworks [16], one use non-linear principal component analysis with optimal encoding [4] [5]. Some researchers prefer confirmatory analysis [14], because this method can be satisfied by a limited number of common factors. In the goal of reducing the arbitrariness in the choice of the method of data reduction, two approaches are used in recent times.…”

Section: ) Critical Assetsmentioning

confidence: 99%

Multidimensional Poverty and Fertility in Congo

Ambapour¹,

Okandza²,

Moussana³

2016

JSS

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According to the well-known hypothesis stated in "The New Home Economics", theory that it associated with the name of Becker, poverty leads to a high fertility. Throughout this text, this hypothesis will be tested using data from the 2005 Demographic and Health Survey of Congo, knowing that poverty will be tackled in a non-monetary and multidimensional approach; and fertility in a parity view, that is to say the number of children a woman gave birth during the five years preceding the survey.

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“…The higher the number of household consumer durable assets, the more durables household assets the individual has. Ownership of these listed household consumer durable assets has consistently been used to demonstrate one's wealth and/or SES creation (Kruk et al, 2008;Sahn and Stifel, 2000).…”

Section: Independent Variablesmentioning

confidence: 99%

The Association Between Household Consumer Durable Assets and Maternal Health-Seeking Behavior in Ghana

Ansong

2015

Women & Health

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This paper examined the association between household consumer durable assets and maternal health seeking behaviour. Several studies suggest that there is a relationship between households' socioeconomic status (SES) and health outcomes. However, SES is a multidimensional concept with other variables that encompass variables such as wealth, education and income. By lumping these variables together as one construct, prior studies have not provided enough insight into possible independent associations with health outcomes. This study used data from the 2008 Ghana Demographic and Health Survey from women aged between 15 and 49 years to examine the association between household consumer durables (a component of SES) and maternal health seeking behaviour (MHSB) in Ghana. Results from a set of generalized linear models on a sub-sample of 2,065 participants indicate that household consumer durable assets are positively associated with antenatal practices such as seeking prenatal care from skilled health personnel, delivery by skilled birth attendant, place of delivery, and the number of antenatal visits. The study discusses implications for health interventions and policies that focus on most vulnerable households.

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Poverty Comparisons Over Time and Across Countries in Africa

Cited by 432 publications

References 7 publications

Social Network Effects on Mobile Money Adoption in Uganda

Social Network Effects on Mobile Money Adoption in Uganda

Multidimensional Poverty and Fertility in Congo

The Association Between Household Consumer Durable Assets and Maternal Health-Seeking Behavior in Ghana

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